Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/24503
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dc.contributor.authorChattopadhyay, R-
dc.date.accessioned2013-12-06T04:26:34Z-
dc.date.available2013-12-06T04:26:34Z-
dc.date.issued2006-03-
dc.identifier.issn0975-1025 (Online); 0971-0426 (Print)-
dc.identifier.urihttp://hdl.handle.net/123456789/24503-
dc.description160-169en_US
dc.description.abstractThis paper reports a brief outline of artificial neural network (ANN) and reviews its application in yarn manufacturing process. The use of neural network in predicting process parameters from known and unknown combination of yarn properties has also been investigated. ANN has been found to be very efficient in predicting process parameters when property combinations are taken from actual observed data. However, when the property set is arbitrary, the prediction is poor. The importance of choosing a feasible combination of input parameters has been highlighted.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.relation.ispartofseriesInt. Cl.8 D02G3/00, G06N3/00en_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJFTR Vol.31(1) [March 2006]en_US
dc.subjectArtificial neural networken_US
dc.subjectPrincipal component analysisen_US
dc.titleApplication of neural network in yarn tnanufactureen_US
dc.typeArticleen_US
Appears in Collections:IJFTR Vol.31(1) [March 2006]

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